Lattice	
Inputting data one pixel at a time (inputtingdata.s).
Image plot (inputtingdata.s).					
Pocket plot (inputtingdata.s or oak103.s).
*Convert to geostatistical data (inputtingdata.s).
Median polish (oak102.s).
Variogram of median polish residuals (oak103.s).

Geostat.
Fit spatial trend by regression and show residuals (oak102.s).
*Smooth onto a lattice (oak102.s).
Classical variogram estimate (inputtingdata.s).
Estimate spherical or rational quadratic variogram (inputtingdata.s).
Simulate a Gaussian Random Field with a given variogram (models1.s).
Fit a polynomial surface (inputtingdata.s).
Kriging (inputtingdata.s).

P.P.
Inputting data with a mouse (inputtingdata.s or pp1.s).
Plot with a map (oak1.s).
*Convert to lattice data of quadrat counts on a grid (oak1.s, pp1.s or pp103.s).
*Store as geostatistical data (oak102.s).
Kernel smoothing (pp1.s or pp103.s).
Smooth onto a regular n1 x n1 grid (oak102.s).
K-function and L-function (pp1.s or pp102.s or pp103.s).
F-function (pp103.s).
G-function (pp103.s).
J-function (pp103.s).
Confidence bounds on the K-function and L-function (pp1.s or pp102.s).
Simulate a Neyman-Scott process, Matern(I) process,  or SSI process (pp102.s).
Fit a pseudo-likelihood model (pp103.s).
Plot background rate and fitted model for the rate (pp103.s).

Marked P.P.
Plot, J-function, K-function, L-function, kernel smoothing (pp104.s).
* Convert to quadrat totals (pp104.s).
Fit a pseudo-likelihood model (pp104.s).
Plot background rate and fitted model for the rate (pp104.s).